Release Notes

ENTERPRISE

Discover the new features, updates, and known limitations in this release of the DC/OS Data Science Engine

Release Notes for DC/OS Data Science Engine version 1.0.2

DC/OS Data Science Engine New Features

  • Updated miniconda version from 4.6.14 to 4.7.12.1

DC/OS Data Science Engine Bug Fixes

  • Fixed LD_LIBRARY_PATH to point to correct version of CUDA libraries
  • Fixed Spark Environment to have SPARK_DIST_CLASSPATH set
  • Fixed Service Account file path to allow notebooks to run from any directory
  • Fixed BeakerX configuration file path to allow BeakerX Spark Magic to work from any directory

DC/OS Data Science Engine Limitations

  • DC/OS Data Science Engine does not support notebook having spaces in the name. It is recommended to use underscore (_) instead of () in the notebook name.

Release Notes for DC/OS Data Science Engine version 1.0.1

DC/OS Data Science Engine New Features

  • Added automation for enabling/disabling verbose logging for Spark resource offers
  • Notebook Docker image is configurable via service options.
  • DC/OS Data Science Engine now stores fetched Hadoop configuration files, hdfs-site.xml and core-site.xml, in $MESOS_SANDBOX/hadoop_conf folder so users can modify them without root privileges.

DC/OS Data Science Engine Bug Fixes

  • Fixed Spark configuration dialog in BeakerX kernel.
  • Fixed folder permissions so users can install new packages with conda or pip.
  • Fixed static resources paths in host mode for components with UI: Spark, History Server, Tensorboard

DC/OS Data Science Engine Breaking Changes

  • CUDA 9 images will no longer be provided with a bundle; CUDA 10 is the only version used for GPU images.
  • jaas_secret option removed from security configuration. extra_spark_secrets should be used instead.

DC/OS Data Science Engine Limitations

  • DC/OS Data Science Engine does not fully support root service user. It is recommended to use the default user nobody.
  • DC/OS Data Science Engine does not support the installation of Python packages on CoreOS. It is recommended to use CentOS.
  • DC/OS Data Science Engine does not support AWS Classic Load Balancer, because it does not support WebSockets. It is recommended to configure load balancers and proxies to allow WebSockets.